Dr James Chan received his B.Sc. degree in Pharmacy and Ph.D. degree in Pharmaceutical Sciences from the National University of Singapore. In 2018, he joined the Skin Research Institute of Singapore where he established a skin-centric metabolomics platform using mass spectrometry tools to investigate chemical and biological perturbations that explain changes in skin phenotypes. He is currently a Junior Principal Investigator at A*STAR, Skin Research Labs.
Skin omics as a tool for pathway discovery and mechanistic investigations.
The skin is a heterogeneous organ that involves cross-talk between many different cell types to maintain skin health and barrier integrity. These processes often involve the secretion of metabolites that act as chemical messengers to relay biological signals and influence various skin phenotypes. Such functional metabolites include energy metabolites, bioactive eicosanoids, natural moisturizing factors, structural ceramides and others. Pathophysiological changes in skin can often be traced back to changes in biochemical pathways, which in turn can be detected by changes in levels of these functional metabolites. They serve as both biomarkers and starting points for further mechanistic investigations.
To profile these metabolites, we use a combination of liquid chromatography-mass spectrometry and spatial omics to quantify and triangulate their localization within skin. Currently we have the following instruments:
• Thermo Scientific Vanquish Duo UHPLC coupled to a TSQ QuantisTM Triple Quadrupole Mass Spectrometer for large scale targeted quantitation
• Waters UPLC, coupled to SYNAPT™ XS High-Resolution Mass Spectrometer (DESI-QTOF) for untargeted metabolomics
• Desorption Electrospray Ionization XS, coupled to SYNAPT™ XS High-Resolution Mass Spectrometer (DESI-QTOF) for spatial metabolomics
• Matrix-assisted laser desorption/ionization, coupled to SYNAPT™ XS High-Resolution Mass Spectrometer (MALDI-QTOF) for spatial metabolomics and proteomics
We believe that both the levels and location of metabolites possess valuable functional information that is biologically meaningful for a heterogeneous organ such as skin, and where warranted we use these tools to preserve the spatial information of skin metabolites and obtain a different perspective of skin biochemistry.
In silico modelling of transdermal penetration and pharmacokinetic modelling.
In collaboration with Drs Freda Lim and Anjaiah Nalaparaju at the Institute of High Performance Computing, we built and validated an in silico mathematical model that is able to predict and simulate the local skin concentrations and systemic absorption of topically-applied actives. Our model is able to account for the effects of different formulations and excipients and estimate the transdermal absorption of test formulations and actives during the design and development stage to identify the best combinations that can be advanced to clinical testing. We combine the in silico model with experimental data from ex vivo Franz cell and tape stripping studies, as well as spatial profiling of skin cross sections where we obtain the layer-by-layer skin concentrations of topical actives, to derive a precise and quantitative prediction of the active amounts in different skin layers which in turn determine their efficacy and safety.
Microbial-host skin communication
Growing evidence indicate that the commensal skin microbes exert a profound influence on skin health through a number of pathways, such as modulating the skin barrier, tilting the pro- and anti-inflammatory balance, influencing cellular proliferation, migration and maturation. However, our current knowledge remains descriptive, and while it is important to characterize the microbial communities associated with healthy and diseased states, to harness the microbiome we need to develop a clear mechanistic understanding of the means by which the skin microbiome exerts its influence. To this end, we focus on (1) deconvoluting the origin of skin metabolites using stable isotope labelling strategies to determine if they are of microbial or host origin; and (2) identifying candidate bioactive microbial metabolites and querying their function through biochemical screens. By building a mechanistic description of the bidirectional microbial-host relationship, we can start to design strategies to intervene and promote a healthy microbiome, and in turn healthy skin.
1. LDH Ta, JCY Chan, GC Yap, CH Huang, EH Tham, EXL Loo, NHA Suaini, LPC Shek, N Karnani, A Goh, HPS Van Bever, OH Teoh, YH Chan, C Lay, J Knol, F Yap, KH Tan, YS Chong, MFF Chong, SY Chan, JG Eriksson, KM Godfrey, ECY Chan* and BW Lee*. Prenatal Diet, Plasma Micronutrients/Metabolome And Inflammatory Status Influence The Development Of Atopic Eczema In Early Childhood. Allergy (November 2022) DOI: 10.1111/all.15573
2. WZ Teo, JY See, S Ramazanu, JCY Chan & XV Wu (2022): Effect of lactic acid fermented foods on glycemic control in diabetic adults: a systemic review and meta-analysis of randomized controlled trials. Critical Reviews in Food Science and Nutrition (September 2022), DOI: 10.1080/10408398.2022.2128032
3. HY Cheng, JCY Chan, GC Yap, CH Huang, DYQ Kioh, EH Tham, EXL Loo, LPC Shek, N Karnani, A Goh, HPS Van Bever, OH Teoh, YH Chan, C Lay, J Knol, F Yap, KH Tan, YS Chong, K Godfrey, ECY Chan, BW Lee and LDH Ta*. Evaluation of stool short chain fatty acids profiles in the first year of life with childhood atopy-related outcomes. Frontiers In Allergy 3 (April 2022) DOI: 10.3389/falgy.2022.873168
4. SPF Tan, ECY Chan and JCY Chan. Predicting tissue concentrations of transport-dependent chemicals using bottom-up physiologically-based biokinetic modelling. Alternatives to Animal Experimentation 38 (April 2021) 253 – 268 DOI: 10.14573/altex.2007151
5. JCY Chan and the OECD Expert Working Group for PBK Modelling. No 331 Guidance document on the characterisation, validation and reporting of PBK models for regulatory purposes. February 2021, ENV/CBC/MONO(2021)1
6. Ta LDH*, JCY Chan*, ECY Chan, BW Lee et al. A compromised developmental trajectory of the infant gut microbiome in atopic eczema. Gut Microbes, 12 (October 2020) 1-12. *Joint first author
7. Thakur A, SPF Tan, JCY Chan. Physiologically-based pharmacokinetic modeling to predict the clinical efficacy of the coadministration of lopinavir and ritonavir against SARS-CoV-2. Clinical Pharmacology & Therapeutics (August 2020), 108(6):1176-1184.
8. L Zhou, JCY Chan, S Chupin, N Gueguen, V Desquiret-Dumas, SK Koh, J Li, Y Gao, L Deng, C Verma, RW Beuerman, ECY Chan, D Milea and P Reynier. Increased protein S-glutathionylation in Leber’s Hereditary Optic Neuropathy (LHON). International Journal of Molecular Sciences 21 (April 2020)
9. JCY Chan, SPF Tan, Z Upton and ECY Chan. Bottom-up physiologically-based biokinetic modelling as an alternative to animal testing. Alternatives to Animal Experimentation 36 (October 2019) 597-612
10. JCY Chan, ACK Soh, DYQ Kioh, J Li, C Verma, SK Koh, RW Beuerman, L Zhou and ECY Chan. Reactive metabolite-induced protein glutathionylation: a potentially novel mechanism underlying acetaminophen hepatotoxicity. Molecular & Cellular Proteomics 17 (October 2018) 2034 – 2050
11. RH Ho*, JCY Chan*, F Hao, DYQ Kioh, BW Lee and ECY Chan. In silico and in vitro interactions between short chain fatty acids and human histone deacetylases. Biochemistry (2017) 56 (September 2017) 4871 – 4878. *Joint first author
12. JCY Chan, DYQ Kioh, GC Yap, BW Lee and ECY Chan. A novel LCMSMS method for quantitative measurement of short-chain fatty acids in human stool derivatized with 12C- and 13C-labelled aniline. J Pharm Biomed Anal. (May 2017) 10;138:43-53.